Analysis of Stress Distribution in Torsional Shear Testing

The research described herein is concerned with the establishment of a specimen geometry that will lead to a more uniform stress distribution in cyclic torsional shear testing. This goal is realized by means of a parametric study using the method of finite elements and a homogeneous, isotropic, linear-elastic soil characterization. The results of these analyses provide a good qualitative measure of the relative effects of the several parameters under consideration. On the basis of the parametric study, design charts are developed which enable an appropriate specimen geometry to be selected for any specified degree of stress uniformity

The Palliative Care-Promoting Access and Improvement of the Cancer Experience (PC-PAICE) Project in India: A Multisite International Quality Improvement Collaborative.

Mentors at seven U.S. and Australian academic institutions initially partnered with seven leading Indian academic palliative care and cancer centers in 2017 to undertake a program combining remote and in-person mentorship, didactic instruction, and project-based learning in quality improvement (QI). From its inception in 2017 to 2020, the Palliative Care-Promoting Accesst and Improvement of the Cancer Experience Program conducted three cohorts for capacity building of 22 Indian palliative care and cancer programs. Indian leadership established a Mumbai QI training hub in 2019 with philanthropic support. In 2020, the project which is now named Enable Quality, Improve Patient care - India (EQuIP-India) focuses on both palliative care and cancer teams. EQuIP-India now leads ongoing Indian national collaboratives and training in QI and is integrated into India's National Cancer Grid. Palliative Care-Promoting Accesst and Improvement of the Cancer Experience demonstrates a feasible model of international collaboration and capacity building in palliative care and cancer QI. It is one of the several networked and blended learning approaches with potential for rapid scaling of evidence-based practices